code: def test_set_random_seed(self):
      def get_model_output():
          model = keras.Sequential(
              [
                  keras.layers.Dense(10),
                  keras.layers.Dropout(0.5),
                  keras.layers.Dense(10),
              ]
          )
          x = np.random.random((32, 10)).astype("float32")
          ds = (
              tf.data.Dataset.from_tensor_slices(x)
              .shuffle(32)
              .batch(16)
          )
          return model.predict(ds)
  
      rng_utils.set_random_seed(42)
      y1 = get_model_output()
      rng_utils.set_random_seed(42)
      y2 = get_model_output()
      self.assertAllClose(y1, y2)
  
file_path: keras/keras/utils/rng_utils_test.py
imports: import numpy
  import pytest
  import tensorflow
  import keras
  from keras import backend
  from keras.testing import test_case
  from keras.utils import rng_utils
label_desc: Use image node_id 1 for calling the TestRandomSeedSetting obj's underlying member method code with example usage: obj.test_set_random_seed() and returns: model